code: def __init__(self, seeds_, radius, mask_img, allow_overlap, dtype):
      self.seeds_ = seeds_
      self.radius = radius
      self.mask_img = mask_img
      self.allow_overlap = allow_overlap
      self.dtype = dtype
  
imports: import warnings
  import numpy
  from joblib import Memory
  from scipy import sparse
  from sklearn import neighbors
  from nilearn import image, masking
  from nilearn._utils import CacheMixin, fill_doc, logger
  from nilearn._utils.class_inspect import get_params
  from nilearn._utils.niimg import img_data_dtype
  from nilearn._utils.niimg_conversions import check_niimg_3d, check_niimg_4d, safe_get_data
  from nilearn.datasets import load_mni152_template
  from nilearn.maskers._utils import compute_middle_image
  from nilearn.maskers.base_masker import BaseMasker, _filter_and_extract
label_desc: Use image node_id 1 to create a new _ExtractionFunctor object  with example: obj = _ExtractionFunctor(seeds_, radius, mask_img, allow_overlap, dtype)